Abstract
Aging and longevity are complex biological processes influenced by genetic, epigenetic, and environmental factors. Bioinformatics has become a powerful tool in studying aging by enabling the integration and analysis of multi-omics data, including genomics, transcriptomics, and proteomics. This article explores the various bioinformatics approaches used to study aging and longevity, focusing on genomic analysis, biomarkers of aging, and computational models of aging processes. We also discuss the challenges and future directions for bioinformatics in aging research, including the integration of diverse data sources and the potential of personalized interventions.
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